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Han S, DiBlasi E, Monson ET, Shabalin A, Ferris E, Chen D, Fraser A, Yu Z, Staley M, Callor WB, Christensen ED, Crockett DK, Li QS, Willour V, Bakian AV, Keeshin B, Docherty AR, Eilbeck K, Coon H. Whole-genome sequencing analysis of suicide deaths integrating brain-regulatory eQTLs data to identify risk loci and genes. Mol Psychiatry 2023; 28:3909-3919. [PMID: 37794117 PMCID: PMC10730410 DOI: 10.1038/s41380-023-02282-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 09/14/2023] [Accepted: 09/20/2023] [Indexed: 10/06/2023]
Abstract
Recent large-scale genome-wide association studies (GWAS) have started to identify potential genetic risk loci associated with risk of suicide; however, a large portion of suicide-associated genetic factors affecting gene expression remain elusive. Dysregulated gene expression, not assessed by GWAS, may play a significant role in increasing the risk of suicide death. We performed the first comprehensive genomic association analysis prioritizing brain expression quantitative trait loci (eQTLs) within regulatory regions in suicide deaths from the Utah Suicide Genetic Risk Study (USGRS). 440,324 brain-regulatory eQTLs were obtained by integrating brain eQTLs, histone modification ChIP-seq, ATAC-seq, DNase-seq, and Hi-C results from publicly available data. Subsequent genomic analyses were conducted in whole-genome sequencing (WGS) data from 986 suicide deaths of non-Finnish European (NFE) ancestry and 415 ancestrally matched controls. Additional independent USGRS suicide deaths with genotyping array data (n = 4657) and controls from the Genome Aggregation Database were explored for WGS result replication. One significant eQTL locus, rs926308 (p = 3.24e-06), was identified. The rs926308-T is associated with lower expression of RFPL3S, a gene important for neocortex development and implicated in arousal. Gene-based analyses performed using Sherlock Bayesian statistical integrative analysis also detected 20 genes with expression changes that may contribute to suicide risk. From analyzing publicly available transcriptomic data, ten of these genes have previous evidence of differential expression in suicide death or in psychiatric disorders that may be associated with suicide, including schizophrenia and autism (ZNF501, ZNF502, CNN3, IGF1R, KLHL36, NBL1, PDCD6IP, SNX19, BCAP29, and ARSA). Electronic health records (EHR) data was further merged to evaluate if there were clinically relevant subsets of suicide deaths associated with genetic variants. In summary, our study identified one risk locus and ten genes associated with suicide risk via gene expression, providing new insight into possible genetic and molecular mechanisms leading to suicide.
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Affiliation(s)
- Seonggyun Han
- Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA.
| | - Emily DiBlasi
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Eric T Monson
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Andrey Shabalin
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Elliott Ferris
- Department of Neurobiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Danli Chen
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Alison Fraser
- Pedigree & Population Resource, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Zhe Yu
- Pedigree & Population Resource, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Michael Staley
- Office of the Medical Examiner, Utah Department of Health and Human Services, Salt Lake City, UT, USA
| | - W Brandon Callor
- Office of the Medical Examiner, Utah Department of Health and Human Services, Salt Lake City, UT, USA
| | - Erik D Christensen
- Office of the Medical Examiner, Utah Department of Health and Human Services, Salt Lake City, UT, USA
| | - David K Crockett
- Clinical Analytics, Intermountain Health, Salt Lake City, UT, USA
| | - Qingqin S Li
- Neuroscience Therapeutic Area, Janssen Research & Development, LLC, Titusville, NJ, USA
| | - Virginia Willour
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Amanda V Bakian
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Brooks Keeshin
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
- Department of Pediatrics, University of Utah, Salt Lake City, UT, USA
| | - Anna R Docherty
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Karen Eilbeck
- Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Hilary Coon
- Department of Psychiatry & Huntsman Mental Health Institute, University of Utah School of Medicine, Salt Lake City, UT, USA
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Harrison PJ, Mould A, Tunbridge EM. New drug targets in psychiatry: Neurobiological considerations in the genomics era. Neurosci Biobehav Rev 2022; 139:104763. [PMID: 35787892 DOI: 10.1016/j.neubiorev.2022.104763] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 05/15/2022] [Accepted: 06/14/2022] [Indexed: 01/11/2023]
Abstract
After a period of withdrawal, pharmaceutical companies have begun to reinvest in neuropsychiatric disorders, due to improvements in our understanding of these disorders, stimulated in part by genomic studies. However, translating this information into disease insights and ultimately into tractable therapeutic targets is a major challenge. Here we consider how different sources of information might be integrated to guide this process. We review how an understanding of neurobiology has been used to advance therapeutic candidates identified in the pre-genomic era, using catechol-O-methyltransferase (COMT) as an exemplar. We then contrast with ZNF804A, the first genome-wide significant schizophrenia gene, and draw on some of the lessons that these and other examples provide. We highlight that, at least in the short term, the translation of potential targets for which there is orthogonal neurobiological support is likely to be more straightforward and productive than that those relying solely on genomic information. Although we focus here on information from genomic studies of schizophrenia, the points are broadly applicable across major psychiatric disorders and their symptoms.
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Affiliation(s)
- Paul J Harrison
- Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK
| | - Arne Mould
- Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK
| | - Elizabeth M Tunbridge
- Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK.
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Powerful and robust inference of complex phenotypes' causal genes with dependent expression quantitative loci by a median-based Mendelian randomization. Am J Hum Genet 2022; 109:838-856. [PMID: 35460606 DOI: 10.1016/j.ajhg.2022.04.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 04/04/2022] [Indexed: 11/22/2022] Open
Abstract
Isolating the causal genes from numerous genetic association signals in genome-wide association studies (GWASs) of complex phenotypes remains an open and challenging question. In the present study, we proposed a statistical approach, the effective-median-based Mendelian randomization (MR) framework, for inferring the causal genes of complex phenotypes with the GWAS summary statistics (named EMIC). The effective-median method solved the high false-positive issue in the existing MR methods due to either correlation among instrumental variables or noises in approximated linkage disequilibrium (LD). EMIC can further perform a pleiotropy fine-mapping analysis to remove possible false-positive estimates. With the usage of multiple cis-expression quantitative trait loci (eQTLs), EMIC was also more powerful than the alternative methods for the causal gene inference in the simulated datasets. Furthermore, EMIC rediscovered many known causal genes of complex phenotypes (schizophrenia, bipolar disorder, and total cholesterol) and reported many new and promising candidate causal genes. In sum, this study provided an efficient solution to discriminate the candidate causal genes from vast amounts of GWAS signals with eQTLs. EMIC has been implemented in our integrative software platform KGGSEE.
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Bittman EL. Anatomical Methods to Study the Suprachiasmatic Nucleus. Methods Mol Biol 2022; 2482:191-210. [PMID: 35610428 PMCID: PMC10752494 DOI: 10.1007/978-1-0716-2249-0_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The mammalian suprachiasmatic nucleus (SCN) functions as a master circadian pacemaker. In order to examine mechanisms by which it keeps time, entrains to periodic environmental signals (zeitgebers), and regulates subordinate oscillators elsewhere in the brain and in the periphery, a variety of molecular methods have been applied. Multiple label immunocytochemistry and in situ hybridization provide anatomical insights that complement physiological approaches (such as ex vivo electrophysiology and luminometry) widely used to study the SCN.The anatomical methods require interpretation of data gathered from groups of individual animals sacrificed at different time points. This imposes constraints on the design of the experiments that aim to observe changes that occur with circadian phase in free-running conditions. It is essential in such experiments to account for differences in the periods of the subjects. Nevertheless, it is possible to resolve intracellular colocalization and regional expression of functionally important transcripts and/or their peptide products that serve as neuromodulators or neurotransmitters. Armed with these tools and others, understanding of the mechanisms by which the hypothalamic pacemaker regulates circadian function is progressing apace.
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Affiliation(s)
- Eric L Bittman
- Department of Biology and Program in Neuroscience & Behavior, University of Massachusetts, Amherst, MA, USA.
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Xiao X, Zhang CY, Zhang Z, Hu Z, Li M, Li T. Revisiting tandem repeats in psychiatric disorders from perspectives of genetics, physiology, and brain evolution. Mol Psychiatry 2022; 27:466-475. [PMID: 34650204 DOI: 10.1038/s41380-021-01329-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 09/16/2021] [Accepted: 09/28/2021] [Indexed: 01/28/2023]
Abstract
Genome-wide association studies (GWASs) have revealed substantial genetic components comprised of single nucleotide polymorphisms (SNPs) in the heritable risk of psychiatric disorders. However, genetic risk factors not covered by GWAS also play pivotal roles in these illnesses. Tandem repeats, which are likely functional but frequently overlooked by GWAS, may account for an important proportion in the "missing heritability" of psychiatric disorders. Despite difficulties in characterizing and quantifying tandem repeats in the genome, studies have been carried out in an attempt to describe impact of tandem repeats on gene regulation and human phenotypes. In this review, we have introduced recent research progress regarding the genomic distribution and regulatory mechanisms of tandem repeats. We have also summarized the current knowledge of the genetic architecture and biological underpinnings of psychiatric disorders brought by studies of tandem repeats. These findings suggest that tandem repeats, in candidate psychiatric risk genes or in different levels of linkage disequilibrium (LD) with psychiatric GWAS SNPs and haplotypes, may modulate biological phenotypes related to psychiatric disorders (e.g., cognitive function and brain physiology) through regulating alternative splicing, promoter activity, enhancer activity and so on. In addition, many tandem repeats undergo tight natural selection in the human lineage, and likely exert crucial roles in human brain evolution. Taken together, the putative roles of tandem repeats in the pathogenesis of psychiatric disorders is strongly implicated, and using examples from previous literatures, we wish to call for further attention to tandem repeats in the post-GWAS era of psychiatric disorders.
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Affiliation(s)
- Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Chu-Yi Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Zhuohua Zhang
- Institute of Molecular Precision Medicine and Hunan Key Laboratory of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China.,Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Zhonghua Hu
- Institute of Molecular Precision Medicine and Hunan Key Laboratory of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China. .,Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China. .,Department of Critical Care Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China. .,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China. .,Hunan Key Laboratory of Animal Models for Human Diseases, School of Life Sciences, Central South University, Changsha, Hunan, China. .,Eye Center of Xiangya Hospital and Hunan Key Laboratory of Ophthalmology, Central South University, Changsha, Hunan, China. .,National Clinical Research Center on Mental Disorders, Changsha, Hunan, China.
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China. .,CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China. .,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
| | - Tao Li
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China. .,Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China.
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